Exploring the Risk Transmission Characteristics Among Unsafe Behaviors Within Urban Railway Construction Accidents
Autor(en): |
Bing Tang
Shengyu Guo Jichao Li Wei Lu |
---|---|
Medium: | Fachartikel |
Sprache(n): | Englisch |
Veröffentlicht in: | Journal of Civil Engineering and Management, 27 Mai 2022, n. 6, v. 28 |
Seite(n): | 443-456 |
DOI: | 10.3846/jcem.2022.16924 |
Abstrakt: |
Various construction accidents are proven to be caused by multiple unsafe behaviors (e.g., wrong use of PPE), but the risk transmission among different behaviors remains unclear. This paper provides insight into risk transmission through behavioral risk chain that leads to accidents from a system safety perspective. To better understand the coupling mechanism of various unsafe behaviors, integrate different behavioral risk chains and present the risk transmission process, a directed-weighted complex network (DWCN) method was adopted. Historical urban railway construction accidents in China are investigated to extract behavioral risk chain. A DW-BRCNA is applied to integrated behavioral risk chain and the behavioral risk transmission characteristics are explored and clarified by the five network properties, including degree and degree distribution, node strength and node strength distribution, average path length and diameter, weighted clustering coefficient and betweenness centrality. The results show that DW-BRCNA has the characteristics of a small-world, scale-free and hierarchical network, indicating that some unsafe behaviors are of greater importance in the process of risk transmission through behavioral risk chains. In addition, risk transmission in critical behavioral risk chains is more potentially to lead to accidents. This study proposed a new perspective of accident causation analysis from risk transmission among unsafe behaviors. It explains the risk transmission characteristics by a DWCN method based on behavioral risk chains. The findings also provide a practical guidance for developing control strategies on sites to prevent risk transmission and reduce accidents. |
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Datenseite - Reference-ID
10679670 - Veröffentlicht am:
17.06.2022 - Geändert am:
17.06.2022